Uses of Class
org.hipparchus.optim.nonlinear.scalar.MultivariateOptimizer
Package
Description
Optimization algorithms for linear constrained problems.
Algorithms for optimizing a scalar function.
This package provides optimization algorithms that require derivatives.
This package provides optimization algorithms that do not require derivatives.
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Uses of MultivariateOptimizer in org.hipparchus.optim.linear
Modifier and TypeClassDescriptionclass
Base class for implementing linear optimizers.class
Solves a linear problem using the "Two-Phase Simplex" method. -
Uses of MultivariateOptimizer in org.hipparchus.optim.nonlinear.scalar
Modifier and TypeClassDescriptionclass
Base class for implementing optimizers for multivariate scalar differentiable functions.ModifierConstructorDescriptionLineSearch
(MultivariateOptimizer optimizer, double relativeTolerance, double absoluteTolerance, double initialBracketingRange) TheBrentOptimizer
default stopping criterion uses the tolerances to check the domain (point) values, not the function values.MultiStartMultivariateOptimizer
(MultivariateOptimizer optimizer, int starts, RandomVectorGenerator generator) Create a multi-start optimizer from a single-start optimizer. -
Uses of MultivariateOptimizer in org.hipparchus.optim.nonlinear.scalar.gradient
Modifier and TypeClassDescriptionclass
Non-linear conjugate gradient optimizer. -
Uses of MultivariateOptimizer in org.hipparchus.optim.nonlinear.scalar.noderiv
Modifier and TypeClassDescriptionclass
Powell's BOBYQA algorithm.class
An implementation of the active Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for non-linear, non-convex, non-smooth, global function minimization.class
Powell's algorithm.class
This class implements simplex-based direct search optimization.